@杨洋MQ Social Network 中 Spammer Detection 方面 都有哪些 中文、英文的数据集？

[haoawesome]

http://www.weibo.com/1214738093/BjP4YcZT2

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related papers

http://ijcai.org/papers13/Papers/IJCAI13-388.pdf Social Spammer Detection in Microblogging

http://conferences.sigcomm.org/imc/2011/docs/p243.pdf Suspended Accounts in Retrospect: An Analysis of Twitter Spam

http://share.iit.edu/handle/10560/2902 SPAM DETECTION IN SOCIAL NETWORKS: A CASE STUDY OF WEIBO

http://dl.acm.org/citation.cfm?id=2501035 Analysis and identification of spamming behaviors in Sina Weibo microblog

[haoawesome]

most related datasets

http://trec.nist.gov/data/tweets/ use that with this dataset

• http://www.infochimps.com/datasets/twitter-spammers-list twitter spammer list

http://plg.uwaterloo.ca/~gvcormac/spam/ TREC 2005- 2007 spam data

• http://plg.uwaterloo.ca/~gvcormac/treccorpus06/ (75MB – english, 60MB chinese) – Spam Corpus 2006

http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/ SMS spam

http://wing.comp.nus.edu.sg:8080/SMSCorpus/overview.jsp

• http://www.corpus4u.org/forum/showthread.php?t=9028 我之前看过，但他们收集的都是正常短信。我还邮件联系过他们，他们说没收集垃圾短信

http://www.ccert.edu.cn/spam/sa/datasets.htm chinese email

more datasets

https://archive.ics.uci.edu/ml/datasets/Spambase UCI dataset 1999

http://www.aueb.gr/users/ion/data/enron-spam/ enron spam email 2006

http://csmining.org/index.php/ling-spam-datasets.html multiple spam datasets (most emails)

http://untroubled.org/spam/ up to 2014 email

https://spamassassin.apache.org/publiccorpus/ email 2004

http://artinvoice.hu/spams/ email

http://www.infochimps.com/tags/spam list of spam datasets

[haoawesome]

问： @杨洋MQ Social Network 中 Spammer Detection 方面 都有哪些 中文、英文的数据集？答： 初步回答：http://memect.co/U19k-Oo 公开的大多是email，中文较老有2006 TREC , 2005 CCERT；英文有Twitter数据集和Spammer列表。近年未公开：berkeley, ASU有Twitter研究; 国内要联系上交大。

http://www.weibo.com/5220650532/Bk2BaFaY2?mod=weibotime

[haoawesome]

最近几个问答也相关 2014-10-16 垃圾邮件分类有什么数据集么? http://t.cn/R7L0GJZ 2014-10-16 有没有垃圾邮件检测的项目啊？ http://www.weibo.com/5220650532/BrOXC1Qkq 2014-10-28 识别垃圾与虚假信息 https://github.com/memect/hao/issues/307

http://www.weibo.com/5220650532/Bvb4pykL8